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phData: Data Engineering
AUGUST 11, 2023
Data engineering in healthcare is taking a giant leap forward with rapid industrial development. However, data collection and analysis have been commonplace in the healthcare sector for ages. Data Engineering in day-to-day hospital administration can help with better decision-making and patient diagnosis/prognosis.
Cloudera
MAY 2, 2022
Companies doing business with Europe need to be aware of their legal obligations — most notably the General Data Protection Regulation (GDPR) — even if they are based elsewhere. There are many reasons to deploy a hybrid cloud architecture — not least cost, performance, reliability, security, and control of infrastructure.
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Cloudera
SEPTEMBER 12, 2022
Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Both obstacles can be overcome using modern data architectures, specifically data fabric and data lakehouse. Unified data fabric.
AltexSoft
FEBRUARY 11, 2023
This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.
Snowflake
AUGUST 21, 2023
With demonstrable success across a range of industries, organizations are increasingly pursuing cutting-edge data mesh architectures to enhance self-service data use. How, then, are modern data teams finding success with the data mesh?
Knowledge Hut
MARCH 28, 2024
This demonstrates the increasing need for Microsoft Certified Data Engineers. In this blog, I will explore Azure data engineer jobs and the top 10 job roles in this field where you can begin your career. They work together with stakeholders to get business requirements and develop scalable and efficient data architectures.
Cloudera
APRIL 13, 2021
Its existing data architecture, however, wasn’t up for the gig. As the data ingestion rate of current business grew to multiple tens of gigabytes per day, the company saw the economic and functional limits of what could be done. The company turned to CDP to streamline migration of critical data workloads to the public cloud.
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